def objective(self, nu):
# compute the availabilities and the objective at nu
self.check_nu(nu)
# compute the combined routing matrix and the combined rate
lam = self.phi + nu
tmp = np.dot(np.diag(nu), self.kappa) + np.dot(np.diag(self.phi), self.delta)
inverse_lam = np.divide(np.ones(self.N,), lam)
r = np.dot(np.diag(inverse_lam), tmp)
# compute the availabilities
pi = r_2_pi(r)
a = pi_2_a(pi, lam)
# compute the objective
obj = np.sum(np.multiply(self.w, a))
return obj, a
def objective(self, nu):
# compute the availabilities and the objective at nu
self.check_nu(nu)
# compute the combined routing matrix and the combined rate
lam = self.phi + nu
tmp = np.dot(np.diag(nu), self.kappa) + np.dot(np.diag(self.phi),
self.delta)
inverse_lam = np.divide(np.ones(self.N, ), lam)
r = np.dot(np.diag(inverse_lam), tmp)
# compute the availabilities
pi = r_2_pi(r)
a = pi_2_a(pi, lam)
# compute the objective
obj = np.sum(np.multiply(self.w, a))
return obj, a
def throughputs(self, eps=1e-8):
# get throughputs by solving the balanced equations before attacks
return r_2_pi(self.routing, eps)
def new_throughputs(self, eps=1e-8):
# get throughputs by solving the balanced equations after attacks
return r_2_pi(self.new_routing, eps)
def throughputs(self, eps=1e-8):
# get throughputs by solving the balanced equations before attacks
return r_2_pi(self.routing, eps)
def new_throughputs(self, eps=1e-8):
# get throughputs by solving the balanced equations after attacks
return r_2_pi(self.new_routing, eps)
